COMPARATIVE ANALYSIS AND MODELING OF IP TRAFFIC IN A CAMPUS NETWORK HETEROGENEOUS

Abstract

With the deployment of new devices, protocols and applications, network traffic is changing to adapt to these trends. Therefore,
it is necessary to analyze the impact over services and resources in data networks. Traffic classification of network is an important requirement to optimize traffic engineering and adequately provision quality of service. In this paper, we analize the
variable packet size of the traffic in an university campus heterogenuos network (wired and wireless) throught the collected data using a novel sniffer that ensures the user data privacy. We separate the collected data in each scenario, by type of traffic,
protocols and applications in order to compare the behavior of packet length. Finally, we estimate the traffic model that
represents this traffic by means of probability distribution and compute its associated numerical parameters.